RE: The Ohio Rural Jobs Act, S. B. No. 209

Transcription

1 9/30/2015 The Honorable Senator Bob Peterson Chairman Ohio Senate Ways and Means Committee 1 Capitol Square, 1st Floor Columbus, OH Dear Chairman Peterson, RE: The Ohio Rural Jobs Act, S. B. No. 209 Thank you for the opportunity to testify in support of S.B. 209, the Ohio Rural Jobs Act. Advantage Capital Partners provides equity and debt financing to established and emerging companies located in communities underserved by conventional sources of capital. Since 1992, the firm has invested more than $1.9 billion in companies from a diverse array of industry sectors, including manufacturing, technology, agribusiness and business services, among others and has primary offices in New Orleans, St. Louis, New York, Austin and California and local offices in a half dozen other states including Ohio. In 2014, Advantage Capital Partners raised a $12.8 million Ohio-based fund under the New Markets Tax Credit program for investment in small businesses. We are in the process of reviewing potential deals and will be making investments over the next four months. To date, we have raised funds in 23 states and D.C. under 25 different state and federal economic development initiatives and have invested in more than 600 unique small businesses. Each state program is unique and we ve found the most impactful programs to be ones where all interests are aligned, new private market investment behavior is incented and a positive return on investment through permanent job creation is a top priority. We believe the Ohio Rural Jobs Act meets these criteria and more. Included as a part of this testimony is a study titled The Economic and Fiscal Impacts of the Ohio Rural Jobs Act (Appendix A). Completed by the nationally recognized Regional Economic Models, Inc. (REMI), the economic impact study analyzed over 200 investments made in small businesses under similar programs across 13 states. This data was used to estimate the impact of the proposed Ohio Rural Jobs Act. While no study can perfectly predict the future, this study used actual financial statements and statistics from a substantial number of real life examples lending the study results additional credibility. Based on the results, the projected return on

2 investment for the state of Ohio, considering both created and retained jobs, is $3.88 of new tax revenue for every $1 of state tax credits. In addition to the REMI report, nine rural investment case studies (Appendix B) from other states have been provided to showcase the types of businesses that could benefit in Ohio. Rural communities represent one of the most underserved geographies in Ohio as it relates to private capital. Based on current PitchBook: Global Private Equity and Venture Capital data, rural Ohio received only 4.7% of all private equity and venture capital investments since 2004 and only 2.6% since 2012 despite representing 18.4% of Ohio s residents. The trend is going in the wrong direction with rural Ohio businesses attracting less than 1/8 th of its expected pro rata share of capital each year. The State of Ohio has over 47 business-focused economic development programs, yet rural areas remain underserved. We urge your support of the Ohio Rural Jobs Act which would provide much needed affordable and flexible risk capital for rural and agribusiness entrepreneurs. Thank you for your time and consideration, Ryan Brennan Managing Director Advantage Capital Partners Advantage Capital Partners is an investment adviser registered under the Investment Adviser Act of Registration does not imply a certain level of skill or training. This release is not intended to be an advertisement subject to the rules under the Investment Advisers Act of

3 The Economic and Fiscal Impacts of the Ohio Rural Jobs Act (ORJA) Prepared by (REMI) Scott Nystrom, M.A. Senior Economic Associate/Project Manager REMI 1717 K St. NW Suite 900 Washington, DC (202) <scott.nystrom@remi.com> Friday, March 20, 2015

4 Executive Summary This study examines the economic and fiscal implications of the Ohio Rural Jobs Act (ORJA) and its implementation of tax credits for rural economic development in Ohio. It relies on relating historical data from other states and investment portfolios to Ohio and then presumes the trends and averages with previous rural credits in other states with adjustments to the local industry mixture hold. Most states with the largest effects from new market tax credits (NMTCs), a similar program to the ORJA without restrictions on geography, have a large degree of involvement from such industries as light- and medium-manufacturers and personal service firms. The former are specialties of rural counties in Ohio. To perform an impact analysis, the direct impacts of credit allocation based on historical trends are inputs into the REMI model, a dynamic, regional model of the state s economy. The results here show the potential for a positive economic impact and a positive benefit-cost ratio (BCR) for the state. If the ORJA proceeds as NMTCs in the rural areas of other states, the $60 million allocation could generate 1,200 to 4,000 new jobs. The range depends on the definition of the jobs, counting either just new jobs created or those jobs created and retained from the funding and investment of capital under the credit program. The results are similar for gross state product (GSP) and personal income, and the extra economic activity is enough to bring in an additional $5 million to $22 million in annual revenue to Columbus budget. Balancing this additional revenue from such sources as personal income and state sales taxes leaves a return on the state budget of between a BCR of 1.1 under most conservative assumptions and 3.8 under the most inclusive of assumptions (including all retained jobs as a part of the direct impact) ). Benefit-Cost Analysis (BCA) and Return-on-Investment (ROI) JOBS CREATED 3% discount 7% discount Present Value of Benefits (revenues) $53.31 $45.25 Present Value of Costs (tax credits) $42.43 $39.36 Net Present Value (NPV) $10.88 $5.88 Benefit-Cost Ratio (BCR) JOBS CREATED/RETAINED 3% discount 7% discount Present Value of Benefits (revenues) $ $ Present Value of Costs (tax credits) $42.43 $39.36 Net Present Value (NPV) $ $ Benefit-Cost Ratio (BCR) p. 1

5 Table of Contents Executive Summary p. 1 Table of Contents p. 2 Introduction pp. 3-4 Economic Impact Results pp. 5-6 o Total Employment p. 5 o Gross State Product (GSP) p. 5 o Real Disposable Personal Income (RDPI) p. 6 Demographic Impact Results p. 6 o Population p. 6 GSP by Industry p. 7 Employment by Industry p. 8 Employment by Occupation pp Fiscal Impact Results p. 11 o Tax Revenues p. 11 o Benefit-Cost Analysis (BCA) p. 11 (REMI) p. 12 The REMI Model pp o Model Structure p. 15 Development of Model Inputs pp o State Data Sources p. 16 o Industry Mixture p. 17 Contact Information p. 18 Notes p. 19 p. 2

6 Introduction This study examines the prospective economic and fiscal impacts of rural business investment credits (RBIC) in the state of Ohio. RBIC programs are similar to new market tax credits (or NMTC); though, RBICs require a concentration of the investment dollars in rural and relatively underdeveloped areas for credit eligibility. An NMTC or RBIC program is a provision in the state or federal tax code to offer incentives for private capital to invest in small businesses, startups, low-income areas, or regions otherwise of economic distress. Ohio and many other states have existing NMTC programs, and they oftentimes include special criteria for a certain quantity of the credit to focus on rural or underdeveloped areas. The federal government has the largest credit through the Community Development Financial Institutions Fund (CDFI Fund), 1 and many states supplement this with their own. With general NMTC programs, the list of states includes Alabama, Alaska, Arkansas, Florida, Illinois, Kentucky, Louisiana, Maine, Mississippi, Nebraska, Nevada, Ohio, Oregon, and Utah. 2 This study will look at the addition of a similar program with a rural focus for the state of Ohio. This study is from the consulting wing of (REMI) based in Washington, DC. 3 This report includes a technical appendix with more details on the raw data and simulations in an appendix, but a short summary of methodology is in this introduction. Given that RBICs are tax credits, there are always questions about their impact on the state s economy and the eventual upshot for the state budget. These questions involve the degree for the attraction of private capital, job creation, new economic activity generated, the fiscal cost of the credit, and the net return-on-investment (ROI) for the state by various metrics. The analysis uses standard statistical techniques and regional modeling to assess such questions for the state of Ohio and the proposed Ohio Rural Jobs Act (ORJA). When modeling a RBIC or a NMTC program, the largest, initial question is to determine the degree of job creation and economic growth from the ensuing private investment. This report addresses this by examining historical data from peer programs and investments in other states. This study uses statistics derived from historical performance to guide the expected level of investments and economic performance for the ORJA. An assorted set of private equity firms provided REMI with portfolio data on past investments and existing firms associated with NMTC programs in rural areas from other states. The data set included the NAICS of the firm, 4 its initial and total state tax credit allocation, and the number of jobs self-reported as created or retained by the companies. Created jobs would include those that came about directly from outside investment aided by the tax credits. Retained jobs include those preserved by outside investment that prevented a firm from downsizing its staff or shuttering entirely. The data set also included a column for rural yes or rural no, and the data for this analysis used only the rural examples owing to the nature of the ORJA s qualification standards. This created 1 U.S. Department of the Treasury, < 2 New Markets Tax Credit Resource Center, < 3 < 4 North American Industrial Classification System (NAICS), or the U.S. Census definition of a collection of like firms in a common industry in competition with one another provided similar goods or services on the market, such as Big Box establishments in a suburb all being part of the Retail (44-45) industry in NAICS, please see, < p. 3

7 an association, or elasticity, of dollars in claimed credits for every job either created or retained in the data. ORJA provides for $45 million in credits to claim over a three-year period. Therefore, historical data forms the backbone of how many new jobs ORJA might create directly before using regional economic modeling to illustrate how this would affect the other businesses and industries in the state as well as Columbus budget. New, expanded, or retained jobs and firms would interact with the general Ohioan economy, which the REMI model illustrates. The REMI model is a dynamic, structural model of custom subnational geographies of the United States. 5 The direct inputs from the analysis of historical data from other states are the backbone to this analysis. Nonetheless, they are only step one before the direct firms and jobs from the ORJA interact supply-chains, payrolls, and the local tax base. The supply-chain effect in the model includes the intermediate sourcing of materials and services from one business from another such as the purchase of glass containers from a glassmaker by a food processor to use to store and ship product. New firms and their suppliers will also create a payroll effect where those working for those businesses will distribute their paychecks as consumption. This spending primary affects consumer-centric industries such as housing, retail, food service, healthcare, entertainment, other services, and the purchase of household implements and durable goods (such as vehicles and furniture). These transactions are a static view of the economy, however, and the REMI model includes more responses to make a dynamic response in the housing market and state budget. Additional payroll and consumer income will induce changes in the housing market and within governmental budgets. For instance, some addition of jobs in rural Ohio may tax the existing housing stock beyond its current capacity (either in raw quantity or in the quality of the houses desired by buyers) because more workers relocate to the area to be closer to work. This creates construction activity for new infrastructure, adding to the number of properties, or puts upward pressure on prices. The combination of the above effects from household income from the labor market, consumption, and the housing market changes the fiscal situation through state income taxes, the state sales tax, and local property taxes, respectively. This technique looking at the underlying change in consumer income, consumption, and behavior and it relates to revenues forms the basis for the fiscal impact results in this report. Given the different layers in the initial data here between jobs created and jobs retained, the results present both as a sensitivity analysis between the most inclusive definition of new jobs created by RBICs (created/retained) or the most conservative (created only). Results here are multifaceted: economic, demographic, and fiscal. The main elements include the impacts on employment, gross state product (GSP), 6 real personal income, and output and employment by the 70-sectors in the version of the REMI model here. Demographic results look at the impact to the state s population as well as the types of jobs created. The fiscal results include the gross amount of new revenues, the net present value of those revenues versus the $60 million worth of tax credits in 2016 through 2018, a benefit-cost analysis (BCA) and ratio (BCR) over a decade window, and some concepts of ROI in terms of jobs and state output. 5 For a high-level introduction, please see, < 6 The equivalent to gross domestic product (GDP) at the state-level p. 4

8 Millions of 2015 dollars Jobs over baseline Economic Impact Results Total Employment 4,500 4,000 3,500 3,000 2,500 2,000 1,500 1, Figure 1.1 The above lines are new jobs in Ohio attributable to the RBIC program. Note these are jobs over the baseline, not job creation, which means there are 1,200 or so new jobs created in Ohio in 2025 and not the cumulative of around 12,000 (10x) after a decade. There is an increase with the initial investments. After that, there is long-term stability or even a slight decline as the productivity of the Ohio economy continues to increase and requires fewer jobs. Gross State Product (GSP) Created - 1,148 1,216 1,248 1,251 1,239 1,227 1,212 1,200 1,193 1,187 Created/Retained - 3,802 4,000 4,076 4,071 4,027 3,978 3,926 3,884 3,858 3,845 $600 $500 $400 $300 $200 $100 $ Created $- $130 $140 $146 $150 $153 $156 $158 $161 $164 $168 Created/Retained $- $408 $436 $454 $465 $472 $479 $486 $494 $503 $513 Figure 1.2 The results for GSP, or the total of new economic activity in the state, mirrors the same pattern as the results for employment. The Ohio economy current has a GSP of around $650 billion, which means the above results represent a 0.2% to a 0.6% increase in the total size of the state s economy with the capital investments under the RBIC program. p. 5

9 Individuals over baseline Millions of 2015 dollars Real Disposable Personal Income (RDPI) $300 $250 $200 $150 $100 $50 $ Created $- $57 $64 $69 $73 $76 $78 $80 $82 $83 $85 Created/Retained $- $189 $210 $225 $235 $243 $249 $254 $258 $264 $270 Figure 1.3 RDPI in REMI is the net of additional income on the labor market, minus taxes, divided by any change in the cost of living. Labor income typically constitutes between 60% and 80% of GSP. The results above are similar where the RBIC program adds enough jobs to generate the GDP results in Figure 1.2 and the personal income results. Demographic Impact Results Population 6,000 5,000 4,000 3,000 2,000 1, Created ,111 1,223 1,322 1,411 1,481 Created/Retained ,608 2,257 2,831 3,321 3,754 4,120 4,437 4,725 4,964 Figure 2.1 The increase in the availability of jobs and additional wages in the state induces what the REMI model terms economic migration households relocating to a new area in search of stronger opportunities on the labor market. Adding a few hundred to a few thousand jobs, thus, adds a similar number of people to Ohio, though lagging the labor market. p. 6

10 Table 1 GSP by Industry (average, millions of 2015 dollars) NAICS Industries Chemical manufacturing $25.3 $26.3 $27.3 $28.4 $29.4 $30.5 $31.7 $32.9 $34.2 $35.5 Construction $14.1 $20.4 $23.5 $24.5 $24.4 $23.7 $22.6 $21.4 $20.5 $19.7 State and local government $18.8 $20.1 $20.9 $21.4 $21.6 $21.8 $22.0 $22.3 $22.5 $22.9 Motor vehicles, bodies, and parts $18.3 $18.8 $19.2 $19.7 $20.2 $20.7 $21.3 $21.8 $22.4 $23.0 Professional and technical services $15.4 $16.6 $17.4 $18.0 $18.5 $18.9 $19.3 $19.9 $20.5 $21.2 Wholesale trade $16.0 $16.6 $17.1 $17.4 $17.8 $18.1 $18.4 $18.9 $19.4 $20.0 Plastics and rubber product $13.1 $13.5 $13.8 $14.2 $14.5 $14.9 $15.3 $15.7 $16.0 $16.4 Retail trade $10.8 $11.7 $12.3 $12.7 $12.9 $13.0 $13.2 $13.4 $13.7 $14.0 Food manufacturing $11.4 $11.6 $11.8 $12.0 $12.2 $12.4 $12.6 $12.8 $13.0 $13.2 Fabricated metal product $11.2 $11.4 $11.7 $12.0 $12.2 $12.5 $12.7 $12.8 $13.1 $13.2 Real estate $8.4 $10.3 $11.6 $12.2 $12.6 $12.8 $13.0 $13.1 $13.3 $13.4 Telecommunications $7.8 $8.2 $8.6 $8.9 $9.2 $9.5 $9.8 $10.1 $10.5 $10.8 Publishing industries, except Internet $7.3 $7.7 $8.1 $8.4 $8.8 $9.2 $9.6 $10.1 $10.6 $11.1 Machinery manufacturing $7.2 $7.4 $7.7 $7.9 $8.1 $8.3 $8.6 $8.8 $9.1 $9.3 Management of companies $7.6 $7.8 $7.8 $7.8 $7.9 $7.9 $8.0 $8.2 $8.5 $8.8 Ambulatory health care services $7.9 $7.8 $7.7 $7.4 $7.2 $7.0 $6.9 $6.8 $6.8 $6.8 Monetary authorities $6.5 $6.7 $6.8 $6.8 $6.7 $6.7 $6.6 $6.6 $6.6 $6.7 Administrative and support services $5.4 $5.7 $5.8 $5.9 $6.0 $6.1 $6.2 $6.3 $6.4 $6.6 Paper manufacturing $5.2 $5.3 $5.4 $5.5 $5.7 $5.8 $5.9 $6.0 $6.1 $6.3 Utilities $4.7 $4.9 $5.2 $5.3 $5.5 $5.6 $5.8 $5.9 $6.1 $6.3 Furniture and related product $3.9 $4.0 $4.2 $4.3 $4.4 $4.5 $4.6 $4.7 $4.8 $5.0 Primary metal manufacturing $3.5 $3.6 $3.7 $3.8 $3.8 $4.0 $4.1 $4.1 $4.2 $4.2 Food services and drinking places $2.7 $3.0 $3.3 $3.5 $3.7 $3.9 $4.1 $4.2 $4.3 $4.5 Hospitals $2.9 $3.0 $3.2 $3.3 $3.4 $3.5 $3.6 $3.7 $3.8 $3.9 Nonmetallic mineral product $2.9 $3.0 $3.2 $3.3 $3.3 $3.4 $3.4 $3.5 $3.5 $3.6 Petroleum and coal products $3.2 $3.3 $3.2 $3.2 $3.1 $3.0 $3.0 $3.0 $3.0 $3.1 Printing and related support activities $2.6 $2.6 $2.7 $2.7 $2.7 $2.8 $2.8 $2.9 $2.9 $3.0 Electrical equipment and appliance $2.3 $2.4 $2.5 $2.6 $2.7 $2.8 $2.9 $2.9 $3.0 $3.1 Insurance carriers and related activities $2.3 $2.4 $2.5 $2.5 $2.5 $2.5 $2.6 $2.6 $2.6 $2.6 Waste management and remediation $2.4 $2.4 $2.5 $2.5 $2.5 $2.5 $2.5 $2.6 $2.6 $2.6 Rental and leasing services $1.8 $2.0 $2.1 $2.2 $2.2 $2.2 $2.3 $2.3 $2.4 $2.4 Oil and gas extraction $2.1 $2.1 $2.1 $2.1 $2.1 $2.1 $2.1 $2.2 $2.2 $2.3 Wood product manufacturing $1.6 $1.7 $1.8 $1.8 $1.8 $1.8 $1.9 $1.9 $1.9 $1.9 Computer and electronic product $2.2 $2.1 $2.0 $1.9 $1.7 $1.6 $1.5 $1.5 $1.5 $1.5 Truck transportation $1.8 $1.8 $1.8 $1.7 $1.7 $1.6 $1.6 $1.5 $1.5 $1.5 Repair and maintenance $1.5 $1.5 $1.6 $1.6 $1.5 $1.5 $1.5 $1.5 $1.5 $1.5 Miscellaneous manufacturing $1.3 $1.3 $1.4 $1.4 $1.4 $1.4 $1.5 $1.6 $1.6 $1.7 Personal and laundry services $1.6 $1.6 $1.5 $1.4 $1.4 $1.4 $1.4 $1.3 $1.3 $1.3 Accommodation $1.2 $1.3 $1.3 $1.4 $1.4 $1.4 $1.4 $1.5 $1.5 $1.5 Nursing and residential care facilities $1.0 $1.1 $1.1 $1.1 $1.1 $1.1 $1.1 $1.1 $1.2 $1.2 Internet publishing and broadcasting $0.8 $0.9 $0.9 $1.0 $1.0 $1.1 $1.1 $1.2 $1.2 $1.3 Beverage and tobacco product $0.7 $0.8 $0.9 $0.9 $0.9 $1.0 $1.0 $1.1 $1.1 $1.1 Securities, commodity contracts $0.9 $0.9 $0.9 $0.9 $0.9 $0.8 $0.8 $0.7 $0.7 $0.8 Educational services $0.6 $0.7 $0.8 $0.8 $0.8 $0.8 $0.9 $0.9 $0.9 $1.0 Warehousing and storage $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 Mining (except oil and gas) $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 $0.8 Performing arts and spectator sports $0.6 $0.6 $0.6 $0.7 $0.7 $0.7 $0.7 $0.7 $0.7 $0.8 Membership associations $0.5 $0.6 $0.6 $0.6 $0.7 $0.7 $0.7 $0.7 $0.7 $0.7 Social assistance $0.4 $0.5 $0.6 $0.6 $0.6 $0.7 $0.7 $0.7 $0.8 $0.8 Scenic and sightseeing transportation $0.4 $0.5 $0.5 $0.5 $0.5 $0.5 $0.5 $0.6 $0.6 $0.6 Amusement, gambling, and recreation $0.5 $0.5 $0.5 $0.5 $0.5 $0.5 $0.5 $0.5 $0.5 $0.5 Broadcasting, except Internet $0.4 $0.5 $0.5 $0.5 $0.5 $0.5 $0.6 $0.6 $0.6 $0.6 Support activities for mining $0.2 $0.4 $0.4 $0.4 $0.4 $0.4 $0.4 $0.4 $0.4 $0.4 Couriers and messengers $0.5 $0.5 $0.4 $0.4 $0.3 $0.3 $0.3 $0.3 $0.3 $0.3 Rail transportation $0.3 $0.3 $0.3 $0.3 $0.3 $0.3 $0.3 $0.2 $0.2 $0.3 Transit and ground passenger $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 Air transportation $0.1 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 Textile mills; Textile product mills $0.3 $0.2 $0.2 $0.2 $0.2 $0.1 $0.1 $0.1 $0.1 $0.1 Forestry, fishing, and hunting $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 Pipeline transportation $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 $0.2 Private households $0.2 $0.2 $0.2 $0.2 $0.1 $0.1 $0.1 $0.1 $0.1 $0.1 Other transportation equipment $0.1 $0.1 $0.1 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 Agriculture and forestry support $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 Water transportation $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 Motion picture and sound recording $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 Museums, historical sites, and parks $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 $0.0 Apparel manufacturing $0.0 $0.0 -$0.1 -$0.1 -$0.1 -$0.2 -$0.2 -$0.2 -$0.2 -$0.2 p. 7

11 Table 2 Employment by Industry (average, over baseline) NAICS Industries Construction State and local government Retail trade Professional and technical services Motor vehicles, bodies, and parts Administrative and support services Food services and drinking places Fabricated metal product Wholesale trade Plastics and rubber product Food manufacturing Ambulatory health care services Chemical manufacturing Furniture and related product Publishing industries, except Internet Machinery manufacturing Management of companies Hospitals Real estate Personal and laundry services Monetary authorities Paper manufacturing Printing and related support activities Nonmetallic mineral product Social assistance Accommodation Wood product manufacturing Nursing and residential care facilities Educational services Telecommunications Membership associations Securities, commodity contracts Repair and maintenance Primary metal manufacturing Waste management and remediation Truck transportation Insurance carriers and related activities Electrical equipment and appliance Amusement, gambling, and recreation Performing arts and spectator sports Warehousing and storage Oil and gas extraction Utilities Miscellaneous manufacturing Private households Rental and leasing services Scenic and sightseeing transportation Computer and electronic product Internet publishing and broadcasting Transit and ground passenger Support activities for mining Broadcasting, except Internet Mining (except oil and gas) Couriers and messengers Petroleum and coal products Forestry, fishing, and hunting Beverage and tobacco product Textile mills; Textile product mills Rail transportation Air transportation Motion picture and sound recording Agriculture and forestry support Water transportation Pipeline transportation Museums, historical sites, and parks Other transportation equipment Apparel manufacturing p. 8

12 Table 3 Employment by Occupation (average, over baseline) SOC Occupations Construction trades workers Other production Metal workers and plastic workers Retail sales workers Material moving workers Assemblers and fabricators Information and record clerks Other installation, maintenance, and repair Business operations specialists Computer Food and beverage serving workers Other office and administrative support workers Secretaries and administrative assistants Motor vehicle operators Material recording, scheduling, dispatching Financial clerks Primary, secondary, and special education Health diagnosing and treating practitioners Top executives Financial specialists Sales, wholesale and manufacturing Engineers Other management Operations specialties managers Building cleaning and pest control workers Health technologists and technicians Cooks and food preparation workers Supervisors of production workers Other personal care and service workers Food processing workers Sales representatives, services Supervisors of office and administrative support Nursing, psychiatric, and home health aides Other protective service workers Vehicle and mobile equipment mechanics Supervisors of sales workers Postsecondary teachers Supervisors of construction and extraction Other education, training, and library Other healthcare support Woodworkers Law enforcement workers Drafters, engineering, and mapping technicians Grounds maintenance workers Printing workers Other sales and related workers Counselors and social workers Other food preparation and serving related Advertising and marketing Other teachers and instructors Electrical and electronic equipment mechanics Media and communication workers Personal appearance workers Textile, apparel, and furnishings workers Art and design workers Lawyers, judges, and related workers Supervisors of food preparation and serving Helpers, construction trades Supervisors of installation and maintenance Other construction and related workers Plant and system operators Supervisors of transportation and material Miscellaneous community and social service Life, physical, and social science technicians Physical scientists Entertainment attendants and related workers Legal support workers Entertainers and performers, sports and related Life scientists p. 9

13 Other transportation workers Extraction workers Fire fighting and prevention workers Supervisors of protective service workers Librarians, curators, and archivists Supervisors of building and grounds cleaning Animal care and service workers Architects, surveyors, and cartographers Social scientists and related workers Media and communication equipment workers Other healthcare practitioners and technical Agricultural workers Mathematical science Occupational therapy and physical therapist Supervisors of personal care and service workers Communications equipment operators Funeral service workers Forest, conservation, and logging workers Baggage porters, bellhops, and concierges Fishing and hunting workers Air transportation workers Rail transportation workers Water transportation workers Religious workers Supervisors of farming, fishing, and forestry Military The categories from Table 1 and Table 2 (in blue and gold, respectively) are with the NAICS classifications from the U.S. Census on like firms in the same industry. Table 3 (in red) works based on the Standard Occupational Classification (SOC), which classifies the job by the type of task rather than the industry of the employer. 7 For instance, a computer or IT professional can work for almost any industry. According to NAICS, one such employee working for a car or aerospace manufacturing firm counts as a manufacturing worker even if their daily tasks would have little to do with the production occupations normally associated with that industry. The same would be true in conceiving of them as a healthcare worker if doing server work or data management for a hospital. The SOC codes above, in red, corrects for this by looking at the type of job and then sorting the results into the categories. The results above concentrate in certain industries for two reasons. Foremost, the economy of rural Ohio heavily relies on the agribusiness supply-chain, including farm itself, chemical manufacturing, transportation of bulk commodities, and food processing and manufacturing. These are many of the industries that the data from other states shows as the ones most likely to receive a boost from NMTC or RBIC. 8 Such states include Florida, Illinois, Louisiana, Missouri, and Mississippi, with the Prairie State and the Show Me State being the closest analogs to the rural Ohio economy. Furthermore, when calculating the inputs for the REMI model, the model results above include an adjustment made for the industry mixture of the Ohio economy. Some of the NMTC data showed industries such as paper manufacturing and petroleum products having a benefit under those programs; however, in order for those industries to benefit, there needs to be the underlying business conditions in a region (a resource endowment, a strong industry cluster, or some other factor) for them to thrive in the first place. The addition of the adjustment to industry mixture increases the initial allocation to industries such as food manufacturing above, which contributes to the degree of the results. 7 < 8 More detail is available in the appendix p. 10

14 Millions of 2015 dollars Fiscal Impact Results Tax Revenues $25 $20 $15 $10 $5 $ Created $- $5 $6 $6 $6 $6 $6 $6 $6 $7 $7 Created/Retained $- $16 $17 $18 $19 $19 $19 $19 $20 $20 $21 Figure 3.1 This illustrates the tax revenue for the state of Ohio associated with the additional business activity, payroll, and consumer spending in the simulations. The pickup for the state is anywhere from $5 million to $21 million per year. This depends on the initial assumption about the type of job counted, which balances against the credit costs below. Benefit-Cost Analysis (BCA) and Return-on-Investment (ROI) JOBS CREATED 3% discount 7% discount Present Value of Benefits (revenues) $53.31 $45.25 Present Value of Costs (tax credits) $42.43 $39.36 Net Present Value (NPV) $10.88 $5.88 Benefit-Cost Ratio (BCR) JOBS CREATED/RETAINED 3% discount 7% discount Present Value of Benefits (revenues) $ $ Present Value of Costs (tax credits) $42.43 $39.36 Net Present Value (NPV) $ $ Benefit-Cost Ratio (BCR) The above shows the calculation of the fiscal benefit (the tax revenues) versus the fiscal cost (the liability represented by the tax credits) versus each other. Under the most expansive definition of job creation, the fiscal benefits of RBICs in Ohio approach 4:1. However, in the conservative case, the state budget is close to a breakeven point. These results are over a decade, which is a typical window for assessing these types of programs in many states (and a standard with such programs federally, though some state do rely on three or five years). p. 11

15 (REMI) REMI is an economics and policy analysis firm specializing in services related to modeling. The headquarters of the firm is in Amherst, MA. Its consulting practice resides in the Washington, DC office. It started as a research project at the University of Massachusetts-Amherst (UMass) by a professor named Dr. George I. Treyz. In the late 1970s, Dr. Treyz developed an economic model to assess the potential impact of expanding and tolling the MassPike, or Interstate 90 from Boston west to Worcester, Springfield, and connecting into the New York State Thruway in Albany. He later generalized the methodology of the Massachusetts model into all states and counties of the United States and incorporated the present firm in The current company provides data, software, technical support, and issue-oriented consulting expertise across the United States. The typical REMI user in a state produces work for state government agencies, a federal department, a public university, a private consulting firm, or policy research groups. Current REMI clients in the state of Ohio include Team Northeast Ohio (Team NEO) 9 and a report on the proposed tax reform measures of Governor Kasich. 10 The REMI Model REMI used a 1-region, 70-sector model of Ohio to perform this analysis. Such a model adds up the state s 99-counties into a complete whole for the whole state. The 70-sectors approximate the 3-digit NAICS codes, which include the basic sectors of the economy (services, healthcare, manufacturing, and the like) at a medium level of detail. The REMI model itself relies on four primary quantitative methodologies. This allows the model to highlight each methodology s strengths while compensating for their weaknesses: 1. Input-output tabulation (IO) 11 At the core of REMI is an input-output table (also known as a Social Accounting Matrix, or SAM). 12 An IO table captures the structure of the regional or national economy in terms of business-to-business transactions, wages, consumption, and can provide the multiplier from an additional dollar of spending or purchase. To provide a classic example, an automobile assembly plant in Michigan will have a lengthy supply chain across the rest of the Midwest and the United States. Vehicle assembly in Michigan requires parts from suppliers in Ohio and Wisconsin. Those suppliers need fabricated and primary metal products from steel mills in Indiana and Pennsylvania, drifting into the MA region. Railroads based in Omaha and Kansas City move final and intermediate products around the Midwest, and Great Lakes boats based in Cleveland or Chicago bring in foreign supplies or iron ore from the Mesabi Range of northern Minnesota via Duluth. An IO model captures the effect of adding a dollar to car demand in Michigan and its echoing through the economy and into other industries. However, IO models have several weaknesses. They are very rigid in the computational sense, have no time horizon (only before and after ), no concepts for the scarcity of 9 < 10 Alex Brill and Christy Robinson, Jobs and Growth Effects of Tax Rate Reductions in Ohio, Matrix Global Advisors, May Also called Leontief modeling after its developer, Wassily Leontief, who won a Nobel Prize for it in 1973, please see, < 12 The raw data for the IO table comes from BLS, please see, Inter-industry relationships (Input/output matrix), < p. 12

16 labor and capital, and no internal concept for the competitiveness of different industries in dissimilar regions. They also sometimes lack trade flows between regions, they have no variables for energy prices or costs, and no adjustments to how the structure of supply chains and the overall economy responds to supply-side shocks. REMI includes other modeling techniques to deepen the representation of the structure of the economy over time and include these various concepts. 2. Computable general equilibrium (CGE) CGE models are a broad classification of models that rely on the principles of equilibrium economics. In essence, the addition of CGE principles to REMI introduces market-based concepts and illustrations of the supply and demand for labor, housing, consumption, commuting, production, intermediate inputs, imports, exports, government spending, and other concepts. The CGE portion of the model demonstrates what happens after all markets have had a chance to clear in relation to each other back to a stable equilibrium. For example, the opening of a large manufacturer of wind turbines near a small city will cause more than just a multiplier at the local and regional level. The new plant will bring jobs with it, and, depending on the size and characteristics of the local labor pool, this will bid the price of labor up in the general economy of the area as more workers find a job at the plant. Certain technical skills may be unavailable locally, so some households will move from other parts of the country in order to work there. This increases the city s population and puts upward pressure on local housing prices, which has the benefit of increasing local property tax revenues for the school board but also discourages others from buying homes. Some households may locate in another city far away. Others will make a calculation based on time, distance, price, and square footage and then locate themselves in a neighboring town with lower housing prices and commute the distance back to the city in order to work there or in the turbine manufacturer. Higher housing prices might also induce a developer to build a new housing subdivision in the area, as well. All of these effects, as well as any consequential loss of competitiveness and output from higher energy costs for commercial and industrial enterprises, are not present in pure IO models but an endogenous part of the CGE structure. 3. New Economic Geography Economic geography is the study of the idea that cities and interconnected industries are the engines of economic growth. REMI utilizes this theory to illustrate how specialized labor pools and industry clusters given a region a competitive advantage relative to its competitors. For instance, for labor inputs, the selection of trained surgeons in cities known for university-attached medical schools or healthcare clusters (such as Baltimore, Boston, and Minneapolis/Rochester, Minnesota) is much higher than cities known more for agricultural services or leisure (such as Helena, Montana). Under ceteris paribus, a hospital in a city like Cleveland or Houston is going to have an easier time finding a qualified, productive worker than a similar facility in Las Cruces, New Mexico or Chattanooga, Tennessee. This forms part of the competitiveness measures, particularly for labor-intensive industries like healthcare, finance, insurance, entertainment, and professional and technical services. The same process is in effect for capital-intensive or intermediate input-reliant firms in terms of their relative access to a concentrated supply chain. These industries tend to cluster on p. 13

17 top of each other in a certain niches across the country, such as with the textiles and furniture industries in the Southeast, agribusiness in the Midwest, and shipbuilding on the Gulf Coast from Texas to Louisiana, Alabama, Mississippi, and western Florida. The size and overall health of these clusters is important to the economic wellbeing of any region or city. Different parts of the United States tend to specialized in a handful of key industries maintaining them is essential to maintaining local growth and the quality of the regional economy and its growth in the long-term. 4. Econometrics REMI uses historical data to determine the parameters necessary to populate the mathematics of the model. This includes estimating elasticity (the implicit slope of supply and demand curves), terms, and time lags on how long it takes an individual market to adjust back to equilibrium. Some markets, such as that for labor, tend to work relatively quickly as people and firms look for jobs and employees while other, such as housing, tend to take more time as buyers, sellers, developers, banks, and regulators are always trying to catch-up to a new set of incentives in regional and national housing markets. Some equations in the model are entirely econometric in nature, and this allows the IO and CGE portions of the model to work with each other in a truly dynamic, multiyear structure with multiple regions. The methodology and equations set in REMI are peer-reviewed and available to the public. 13 The initial publications by REMI s founder, Dr. George I. Treyz, and his team have appeared in such publications as the Journal of Regional Science, 14 the Review of Economics and Statistics, 15 and the American Economic Review. 16 The data inside REMI comes from public data agencies such as the BEA, BLS, EIA, U.S. Census, the U.S. Department of Defense, the U.S. Department of Education, and several other sources. 17 Trends in the macroeconomic portion of the model are from the BLS industry forecast and the Research Seminar in Quantitative Economics (RSQE) at the University of Michigan-Ann Arbor. 18 This all provides the data and methodologies for running exogenous policy simulations in the REMI model. The fiscal information in these simulations came from the online data of the Ohio Department of Taxation by revenue source, type, and any major changes over time. 19 This becomes part of an effective rate basis over the information in the REMI model. For instance, if the historical correlation between personal income growth in Ohio and revenues to the state personal income taxes every $100 produces $1 in tax revenues, this becomes an effective rate of around 1% (though the historical one is closer to 4% or 5%). The same is true of states sales taxes and some 13 For the full PDF of model equations, please see, < 14 Dan S. Rickman, Gang Shao, and George I. Treyz, Multiregional Stock Adjustment Equations of Residential and Nonresidential Investment in Structure, Journal of Regional Science, Vol. 33 (2), 1993, pp George I. Treyz, Dan S. Rickman, and Michael J. Greenwood, The Dynamics of U.S. Internal Migration, Review of Economics and Statistics, Vol. LXXV, No. 2, May 1993, pp Please see, < 17 For a full accounting of the data sources and estimation procedures in the REMI model, please see, < _Procedures.pdf> 18 Their homepage on the Michigan and American economies is here, < 19 < p. 14

18 other business taxes and fees. The detailed underlying structure of the REMI model allows for this assessment of the tax revenues and their changes, which is part of the flowchart diagram in Figure 3.1 on the REMI model structure. Figure 4.1 This shows the explicit structure of PI + with cause-and-effect linkages between different concepts and sectors of the economy and demographics. Each block in the above structure of Figure 5.7 describes a different portion of the economy. Block 1 is the macroeconomics of the model with final demand and GDP by component. The calculations in Block 2 make up the business perspective on the economy where firms will maximize profits by minimizing costs in hiring decisions (employment) and capital (their investments). Block 3 is a full demographic model with natural changes, labor mobility within the United States, and international migration and emigration. Block 3 also includes the interactions of households with the general economy through labor force participation, wages, and consumer spending. Block 4 introduces equilibrium concepts to the labor market concepts, the cost of living (including energy prices), and production costs (for labor, capital, fuel inputs, and intermediate goods). Block 5 illustrates the competitiveness of a region with explicit regional purchase coefficients (RPCs), which quantify how likely an area is to keep imports away while moving its own exports out to other regions and countries. p. 15

19 Development of Model Inputs The primary data set for the inputs to these simulations covered alike NMTC policies in other states and how other firms in those states developed in terms of credit allocation, industrial mixture, and jobs created or created/retained. 12% 3% 24% 3% 1% Alabama 3% 4% 3% Arkansas Florida 16% Illinois Kentucky Louisiana Maine 12% Missouri Mississippi Nebraska 14% 3% Nevada Oregon 2% Wisconsin Figure 5.1 The above pie graph shows the home states of the example projects. In total, there were over 200+ projects in the portfolio sample from several investment firms. These are all states with some version of an NMTC or RBIC programs, though some are more extensive than the others are. Semi-urban, non-coastal, and Midwestern states feature heavily in this mixture, including large samples from Illinois, Missouri, and Gulf Coast states such as Florida, Louisiana, and Mississippi. These states have a large number of rural projects and have economies with structures similar to Ohio, particularly with the Midwestern states. The data provided included the NAICS, jobs created, jobs retained, rural status (yes/no), and the state allocation for each project. First, we removed the examples for urban areas to leave only the examples from rural areas. The ORJA only allows for qualifying credits in rural areas, hence this keeps the statistical sample closer to the anticipated reality in the Cyclone State. Dividing the size of the credit by the number of jobs by industry produced a factor of the average number of jobs per dollar of credit or the average amount in credits needed to produce a job. This implicit elasticity helped drive the inputs. For instance, if the rural machinery firms in the data sample received a total of $5 million in credits but generated 50 jobs, then the average cost per job in the same was $100,000 each. To determine how much of the allocation went between the various industries, the simulations used a simple proportion (for instance, if the total was $10 and Industry Q received $2, then 20% of all allocations flow to Industry Q and its jobs) save for a small adjustment made for Ohio s industry mixture. We multiplied the projected allocation by Ohio s location quotient (LQ), relative to the nation, to bias the allocation intentionally towards industries with larger concentrations in Ohio and away from smaller ones. p. 16

20 Fabricated metal product Food manufacturing Chemical manufacturing Motor vehicles, bodies, and parts Wholesale trade Professional and technical services Plastics and rubber product Furniture and related product Machinery manufacturing Nonmetallic mineral product Accommodation Electrical equipment and appliance Retail trade Food services and drinking places Printing and related support activities Insurance carriers and related activities Waste management and remediation Personal and laundry services Publishing industries, except Internet Primary metal manufacturing Miscellaneous manufacturing Wood product manufacturing Paper manufacturing Scenic and sightseeing transportation Ambulatory health care services Telecommunications Educational services Monetary authorities Internet publishing and broadcasting Oil and gas extraction Petroleum and coal products Amusement, gambling, and recreation Broadcasting, except Internet Construction Social assistance Computer and electronic product Nursing and residential care facilities Hospitals Warehousing and storage Repair and maintenance Support activities for mining Motion picture and sound recording Performing arts and spectator sports Apparel manufacturing Water transportation Utilities Truck transportation Transit and ground passenger Textile mills; Textile product mills Securities, commodity contracts Rental and leasing services Real estate Rail transportation Private households Pipeline transportation Other transportation equipment Museums, historical sites, and parks Mining (except oil and gas) Membership associations Management of companies Forestry, fishing, and hunting Couriers and messengers Beverage and tobacco product Air transportation Agriculture and forestry support Administrative and support services 0% 1% 2% 3% 4% 5% 6% 7% 8% 9% 10% Figure 5.2 The above is the allocation of the $60 million in total credits accounting for Ohio s industry mixture. Industries with a heavy presence in Ohio beforehand such as food manufacturing and machinery manufacturing feature heavily. This is to Ohio s benefit; given these are common industries to find in a NMTC portfolio throughout the United States. p. 17

21 (REMI) 1717 K Street NW Suite 900 Washington, DC (202) Scott Nystrom 20 received his B.A. in history, his B.S. in economics, and his M.A. in economic history from Iowa State University 21 in Ames, IA. He has worked for REMI since 2011, and he is the main point of contact in its Washington, DC office for training, technical support, and for economic consulting. Mr. Nystrom works on a daily basis with clients across the United States and the rest of the world in state government, federal organs, provincial authorities, regional councils, consulting firms, universities, foundations, and non-profit research groups. His major projects have included economic analyses of the federal fiscal cliff, 22 Keystone XL pipeline, 23 the $500 billion long-range regional plan for Southern California Association of Governments (SCAG), 24 and Medicaid expansion (with county-level details) in North Carolina. 25 His work on carbon taxes includes similar analyses for Massachusetts, Washington, California, and at the national-level for Citizens Climate Lobby (CCL) in concert with Synapse Energy Economics 26 out of Cambridge, Massachusetts. His other responsibilities include integrating energy models with REMI PI +, modeling transportation, commuting patterns, and business development and client service travel throughout Canada and the United States. 20 Please see, < 21 < 22 Scott Nystrom, Chris Brown, and David Brown, Cheating the Future: The Price for Not Fixing Entitlements, Third Way, February 2013, < _Cheating_the_Future_The_Price_of_Not_Fixing_Entitlements.pdf> 23 Scott Nystrom and William W. Wade, The Keystone XL Pipeline: REMI Estimates of Economic Impacts from Construction and Operations based on the Keystone Record, Energy and Water Economics, February 29, 2012, < 24 Scott Nystrom and Zilin Cui, < 25 Sara Wood, Business Brief: Study shows expanding Medicaid would benefit NC economy, National Public Radio (NPR), February 18, 2013, < 26 < p. 18

22 Notes p. 19

23 NEW MARKETS CASE STUDY COMPANY ALGENT, a division of ALGIX, handles the collection, drying and milling of algae used in algae-blended biodegradeable thermoplastics for the use in extrusion, compounding, injection molding, film casting and other thermoplastic conversion techniques. ALGIX was started in 2010 as a spin-off from of technology developed at the University of Georgia. In early 2012, ALGIX secured a world-wide exclusive license for algae-based thermoplastics. The bio-based resins have applications in packaging, agricultural products, carpeting, personalcare products, consumer electronics and automotive applications. INVESTMENT In 2013, ALGENT received $3.9 million in connection with the Alabama and federal New Markets programs. The funding enables ALGENT to purchase 30 additional algae collection and drying equipment machines which will increase its product significantly. As a start-up company, ALGIX was unable to obtain funding from any traditional sources of capital. This funding will serve as growth capital. IMPACT As a start-up company, ALGIX was unable to obtain funding from any traditional sources of capital. The New Markets funding will enable ALGENT to hire nine new employees within the first year while it focuses on gathering algae to produce larger amounts of scientifically engineered resins. Description Algae Based Biodegradeable Plastics Location Browns, AL New Markets Investment $3.9 million Economic Impact Jobs Created 5 Jobs Retained 13 Community Statistics Unemployment Rate 31.7% Poverty Rate 45% Non-Metro Due to the unique financing option of the New Markets tax credits, ALGIX was able to open an additional facility in Mississippi that manufactures the algae resins The financing of both of these projects enables AGLIX to control all steps involved in creating the algae based resins, saving it about a million dollars a year and enabling it to monitor quality control. Alabama New Markets Development Act Enacted in 2011, the Alabama New Markets Development Act encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Alabama s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. October 2014

24 NEW MARKETS CASE STUDY COMPANY ASPEQ Holdings, Inc. is the parent company of INDEECO. Established in 1929, INDEECO designs and manufactures a complete line of heating equipment, including space heaters, industrial component heaters and electronic controls for commercial, industrial and marine markets located domestically and internationally. INDEECO maintains control over each step of the manufacturing process, crafting heating elements, fabricating sheet metal and building electronic controls. INVESTMENT Since 2008, ASPEQ Holdings has received $14 million in financing raised in connection with the federal and Missouri New Markets programs. Both programs are designed to stimulate economic growth in communities that historically have been underserved by traditional sources of capital. The current owners of INDEECO were looking for a superior financing structure that would enable them to buy the company from second generation owners, and they needed access to flexible capital that would both facilitate the transition and foster new expansion. Description Heater Component Manufacturer Location Cuba, MO New Markets Investment $14 million Follow-on Capital Attracted $34 million Economic Impact Jobs Created and Retained 315 Company-wide Community Statistics Unemployment Rate 6.9% Poverty Rate 17.9% IMPACT The New Markets funding enabled INDEECO to sustain and transform the business through the recent recession. Since the initial investment was made in 2008, it has retained 66 employees at its Cuba location and created 106 jobs company-wide, for a current total of 315 employees. INDEECO reported its best earnings in the quarter following the investment, and the business continues to grow dramatically. INDEECO has purchased two additional businesses and consolidated some of the operations in northeastern Missouri, bringing jobs and an economic boost to the rural town of Monroe City. The company has attracted $34 million in follow-on capital since the New Markets investment. Missouri New Markets Tax Credit Program Enacted in 2007, the Missouri New Markets Tax Credit program encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Missouri s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. December 2014

25 NEW MARKETS CASE STUDY COMPANY Excel Boat Company is a boat manufacturer based in Mountain View, AR. Founded in 2009 to focus on shallow water boats, Excel Boat eventually ventured into the fishing boat market targeting serious hunters and fisherman. The company has grown to produce a full line of sport utility boats ranging from feet with the ability to carry a multitude of engines. INVESTMENT In August 2014, Excel Boats received a $1.61 million dollar investment facilitated through the Arkansas New Markets Jobs act and the federal New Markets program, both of which stimulate economic growth in communities that historically have been underserved by traditional sources of capital. The funding will provide Excel Boats with ample working capital, enabling the company to refinance expensive debt, purchase new equipment and provide additional training for new employees. IMPACT A tornado ripped through Mountain View, Arkansas in 2008 and in the process destroyed a local boat manufacturing company. With a skilled workforce known for their boat building capabilities in the area, then managers Glenn and Sharleen Foreman were determined to bring a boat manufacturing company back to the area. After opening Excel Boats in July of 2009, business led them to begin manufacturing a full line of sport utility boats. As their company continued to grow, local lenders were unable to provide Excel Boats with the amount of funding they need at terms that were beneficial to the company and their growth. The New Markets funding provided the company with an affordable financing option enabling them to purchase equipment and focus on their expansion. The investment supported the retention of 40 jobs and the creation of an additional 5-10 jobs immediately. The company plans to hire a total of 35 jobs over the next 14 months. Description Boat Motor Manufacturing Location Mountain View, AR New Markets Investment $1.61 million Economic Impact Jobs Created 35 Jobs Retained 40 Community Statistics Unemployment Rate 6.5% Poverty Rate 28.3% Arkansas New Markets Program Enacted in 2013, the Arkansas New Markets Jobs Act encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Arkansas s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. October 2014

26 NEW MARKETS CASE STUDY COMPANY GAME Equipment is an agricultural machinery manufacturer and distributor located in rural Louisiana. In 2002 John Deere ceased production of pineapple, vegetable and kenaf harvesting product lines. GAME was able to obtain rights to manufacture the discontinued machinery lines and fill the production gap. In 2007, GAME became an official John Deere dealer/distributor, which allows it to utilize Deere parts and suppliers while adding continuous sugar cane loaders to GAME s offerings. The company exports its locally made products internationally, most recently to a company in Nigeria. INVESTMENT Since 2010, GAME Equipment has received $4.18 million. This investment was made in large part through the federal New Markets program and the Louisiana New Markets Development program. These programs stimulate economic growth in communities that historically have been underserved by traditional sources of investment capital. Description Agricultural Machinery Manufacturer Location Napoleonville, LA New Markets Investment $4.18 million Economic Impact Jobs Created 19 Jobs Retained 21 Community Statistics Unemployment Rate 9.95% Poverty Rate 35.46% IMPACT At a time when GAME needed additional funding for equipment purchases, its traditional lender refused to extend their line of credit. The New Markets financing provided the funding needed to maintain operations and retain 21 full-time employees. Since receiving the investment, GAME has hired an additional 19 employees. Louisiana New Markets Jobs Act Enacted in 2006, the Louisiana New Markets Jobs Act encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Louisiana s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. October 2014

27 NEW MARKETS CASE STUDY COMPANY Hybrid Plastics is a nanotechnology company that manufactures a chemical additive that can increase the strength and longevity of a wide range of products. This additive, called Polyhedral Oliogomeric Silsesquioxane (POSS ), was originally developed in an Air Force Research Lab by Dr. Lichtenhan and Dr. Schwab. The team has since formed Hybrid Plastics and started commercializing POSS technology. INVESTMENT In 2013, Advantage Capital Partners committed to investing a total of $500,000 in Hybrid Plastics in connection with the Mississippi Small Business Investment Credit Act (MSBIC), an economic growth and development program focused on providing capital to small businesses. The funding is part of a $5 million investment round to advance the commercialization of POSS and support the working capital needs associated with Hybrid Plastic s expected growth. Description Nanotechnology Manufacturer Location Hattiesburg, MS New Markets Investment $500,000 Economic Impact Jobs Created 20 Jobs Retained 12 Community Statistics Unemployment Rate 12.8% Poverty Rate 36% IMPACT Commercializing this new product will require Hybrid Plastics to expand its staff as production ramps up. The New Markets investment will allow the company to retain its 20 current employees and hire 10 more, increasing its staff to 30. Hybrid also brings a highly technical industry to the area and provides the potential for increased employment. Mississippi Equity Investment Tax Credit Program Enacted in 2007, the Mississippi Equity Investment Tax Credit program encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Mississippi s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. November 2014

28 NEW MARKETS CASE STUDY COMPANY Integrated 3D is focused on the industrial production of finished, high-value, structurally complex parts using 3D and advanced manufacturing technologies. Using the latest in production-capable additive laser sintering technology machinery, the company manufactures finished parts in both metal and plastic that have the structural integrity for immediate use or for insertion into assemblies. Integrated 3D is a certified Oregon Emerging Small Business (ESB) and Woman-owned Business Enterprise (WBE) partnership. INVESTMENT In 2014, Integraded 3D received $1.7 million in funding through the Oregon and federal New Markets programs. The funding provides Integrated 3D with much needed start-up capital to purchase equipment and fund the early stages of the company. Description 3D Parts Manufacturer Location The Dalles, OR New Markets Investment $1.7 million Economic Impact Jobs Created 6 Community Statistics Unemployment Rate 8.7% Poverty Rate 12.3% IMPACT As a start-up company in the technology sector, finding funding was extremely difficult for Integrated 3D. After being turned away by a number of financial institutions, the New Markets funding enabled the company founders to continue pioneering the world of 3D manufacturing, a technology that is still in its infancy. Additionally, the company has created a total of 6 jobs and plans to grow to 12 over the next two years. Oregon Low Income Communities Jobs Initiative Enacted in 2011, the Oregon Low Income Community Jobs Initiative encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Oregon s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. December 2014

29 NEW MARKETS CASE STUDY COMPANY Kentucky Chrome Works manufactures luxury alloy wheels and is the exclusive chrome plate supplier for the Corvette. In 2009, Kentucky Chrome Works (KCW) began adding chrome plating to RONAL Speedline wheels. Switzerland-based RONAL is the preferred supplier to the top names in the automotive industry. KCW and RONAL provide chrome-plated aluminum alloy wheels for luxury vehicles, supplying more than 4 million wheels a year to General Motors, BMW, Volkswagen, Mercedes and Fiat. INVESTMENT In January 2012, Kentucky Chrome Works received $3 million in funding. The funds were raised in connection with the Kentucky New Markets Development program, which strengthens and stimulates economic growth in communities historically underserved by traditional sources of capital. Description Luxury Allow Wheels Manufacturer Location Horse Cave, KY New Markets Investment $3 million Economic Impact Jobs Created 11 Jobs Retained 44 Community Statistics Unemployment Rate 8.73% Poverty Rate 23% IMPACT The New Markets financing enabled Kentucky Chrome Works to expand its production line and secure muchneeded working capital. The financing enabled the company to hire 11 new employees at the business and retain all existing 44 employees. Kentucky New Markets Development Program Enacted in 2010, the Kentucky New Markets Development program encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Kentucky s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. October 2014

30 NEW MARKETS CASE STUDY COMPANY Quoddy is a high-end, hand sewn shoe manufacturer based in Lewiston, Maine. Established over 100 years ago, Quoddy offers many varieties of shoes, boots and moccasins through various retailors such as J Crew as well as online stores. CEO John Andreliunas, a long-time executive in the footwear industry, joined Quoddy in 2009 and rejuvenated the company, tripling sakes over the last four years. INVESTMENT The $500,000 funding provided through the federal and Maine New Markets programs was critical to the continued growth at Quoddy. Quoddy has focused on developing brand recognition and improving the craftsmanship of the product, opening doors in the wholesale channel for the company. Quoddy has had great success over the past few years, but the the company needed additional funds to build its sales function and brand awareness. The New Markets funding provided that capital and will support continued growth for the company. Description Hand-sewn Shoe Manufacturer Location Lewiston, ME New Markets Investment $500,000 Economic Impact Jobs Created Approximately 20 Jobs Retained 37 Community Statistics Unemployment Rate 16.7% Poverty Rate 28.4% IMPACT The New Markets capital has allowed Quoddy to retain all 37 of its employees. With the increase in funds for sales, the company hopes to add an additional 20 jobs over the next 18 months. The importance of this investment is deeper than the impact on Quoddy. Historically, the Maine shoe industry supported over 30,000 jobs. Today, it is down to approximately 1,000 due to importation of shoes and closure of many local shoe manufacturing plants. Keeping Quoddy and its leather shoe production in Maine has been very important to the local economy. Maine New Markets Capital Investment Tax Credit Program Enacted in 2011, the Maine New Markets Investment Tax Credit program encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Maine s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. July 2014

31 NEW MARKETS CASE STUDY COMPANY Vineburg Machining, Inc. is a veteran-owned, full service precision machine shop providing quality services for longterm customers ranging from local and federal governmental agencies; commercial OEMs; medical, architectural, beverage and automotive companies; and semi-conductor and drone component manufacturers. Working with all types of metals, the company produces high-quality parts from its CNC lathe and mills and provides high end CNC milling and turning. INVESTMENT In 2014, Vineburg Machining received $2.75 million in federal and Nevada New Markets funding, both of which stimulate economic growth in communities that historically have been underserved by traditional sources of capital. The funding will serve as growth capital to improve the company s production capabilities. IMPACT The New Markets funding will enable the company to purchase new equipment and acquire and add improvements to the current facility. As Vineburg diversifies its customer base and sales increase, the funding will ensure that Vineburg can meet demand for its products, allowing the company to handle a much heavier workload. The new equipment will increase efficiency through the use of robotics. The company will retain its 36 current employees and expects to create 10 additional jobs. Description Full Service Precision Machine Shop Location Mound House, NV New Markets Investment $2.75 million Economic Impact Jobs Created 10 projected Jobs Retained 36 Community Statistics Unemployment Rate 7.6% Poverty Rate 30.1% Nevada New Markets Jobs Act Enacted in 2013, the Nevada New Markets Jobs Act encourages investment in promising small businesses located in distressed communities throughout the state. Modeled after the federal New Markets Tax Credit program, the goal of the state program is to attract large, long-term investors to Nevada s low-income communities, promoting new expansion, creating new job opportunities and building on existing growth in the state. December 2014